Caldwell Memorial Hospital’s supply chain was struggling, as many hospital operations do, with multiple stock locations, excess and often incorrect inventory, and low accountability for what was on the shelves.

So the hospital’s leaders took action, and their successful initiative provides several steps that other providers may want to consider, too.

#1Use Lean thinking

Caldwell leaders looked to their prior experience with Lean management tools to guide their efforts in the supply chain. A value stream assessment helped them pinpoint specific challenges, while data collection and analysis helped them develop a strategic plan for tackling them. This critical prep work revealed several key areas of focus: inventory visibility, demand flow optimization and management of physician preference items.

#2Get visual

First up: inventory visibility and demand flow optimization. By introducing a new, Lean-based visual replenishment system, Caldwell gained the transparency needed to consolidate supplies, eliminate excess inventory and lower distribution costs. Plus, clinicians no longer had to spend valuable time managing supplies when they should be with patients. The combined annual savings from these initial activities totaled more than $3 million.

#3 Reign in requests

Next on the list: physician preference items. From supplies to lab resources to room and board, no two Caldwell physicians seemed to utilize assets in quite the same way. And these variations were adding up.

Digging into and analyzing resource usage data allowed Caldwell to break down the costs by clinician, case and location. This revealed just how much the inconsistency was costing the hospital — more than $4 million — and what Caldwell needed to do to convert those costs into cost-saving opportunities.

Results:

If you’d like more information on how this hospital achieved its remarkable result, please reach out to us.You can also read the full case study here.

An efficient revenue cycle has always been an important factor in the success of a healthcare organization. But in today’s complex and dynamic industry, where value-based reimbursement models are becoming the norm, streamlining the flow of money from payers to providers may be more important than ever.

That streamlining is just what Mountain States Health Alliance (MSHA) accomplished. Faced with looming financial challenges, leaders at this Tennessee health system sought a way to reduce expenses, and withstand financial pitfalls for the long term.

By implementing a Lean revenue cycle management (RCM) process, MSHA:

How did do they do it?

MHSA leaders did it through improved communication, transparency and consistency among departments, and the adoption of Lean tools for continuous process improvement.

Since RCM affects every patient in every department, MSHA had to tear down the walls separating the front end (scheduling, registration, financial counseling), the middle (medical records, coding, billing) and the back end (claim drop, liability, accounts receivable).

Daily huddles brought staff members together to discuss key metrics and share information. Progress was tracked on daily improvement boards that were visible to anyone. And Rapid Improvement Events helped staff members get a handle on the interconnectedness of their work, which in turn helped them identify redundancies, reduce variation and waste, and create standards of work.

Like most health systems, Indiana University Health System (IU Health) leaders knew they had large amounts of valuable data stored throughout the organization. The challenge for the largest health system in Indiana was how to use the often-segmented data to quickly identify opportunities for cost controls and financial decision making, especially at the regional level.

To meet this challenge, the system pulled together a results-driven group called the Profitability & Utilization Support Hub (PUSH), made up of experts in revenue cycle, supply chain, clinical operations, labor analytics and more. The team’s charter: Make data-driven recommendations that could eventually drive operational and financial improvements.

The PUSH group began to identify opportunities by leveraging a comprehensive comparative database. The robust and detailed benchmarks allowed the team to see where their organization stood compared to peers.

Here are just three examples of how the team incorporated performance benchmarking to fuel its recommendations:

#1 Reducing above-average telemetry usage

The group proactively found that telemetry usage at one of the system’s hospitals was 70 percent higher than the comparison group median. The PUSH team recommended a review of the hospital’s electronic medical record order set and staffing ratios, which led to changes. The hospital’s telemetry utilization was reduced to the comparison group median within three months.

#2 Increasing oncology patient volume

The health system had recently converted one of its hospitals into an outpatient facility offering emergency department (ED) and oncology services. Using comparison data, the team discovered an imbalance between oncology patient levels and staffing levels. Leadership acted quickly and launched a campaign to increase oncology patient and provider volumes to align with staffing levels.

#3 Boosting ED capacity

The chief financial officer of an IU Health hospital asked the PUSH group for guidance to figure out why ED visits were declining even though staff reported full capacity. The data showed the hospital was efficiently using its available space — treating 20 more ED patients per day than the comparison peer average — but it had six fewer treatment spaces. Based on that insight, the hospital received approval to expand to accommodate 25 more visits per day.

If you’d like more information on how the health system achieved these remarkable results, please reach out to us.

When you discover your mortality rates for stroke, pneumonia and heart failure aren’t where they need to be, what do you do?

The quality team at Carson Tahoe Health, a health system based in northern Nevada and eastern California, recently faced that challenge — and knew they had to answer two key questions: why is this happening and what can we do about it?

After a concentrated chart review, the health system discovered that the majority of patients who died in their care were at the end stages of their diseases.

Recent studies had pointed to the implementation of palliative care as a way to improve patient care and lower mortality rates. So to test the theory in their own environment, Carson Tahoe Health decided to roll out an inpatient care protocol in which hospitalists refer patients with end-of-life issues to a palliative care physician.

Comparing outcomes to determine progress

Using a clinical performance monitoring and benchmarking solution, the quality team was able to analyze several metrics, focusing on heart failure and chronic obstructive pulmonary disease (COPD) diagnosis-related groups in end stages of the diseases.

They tracked two groups of patients: those who participated in the palliative care protocol and those who did not. That way, cost, utilization, readmission, length of stay and other comparisons could be made.

The health system gained some key insights on the value of palliative care:

To see if they could move the dial even further on care improvement, the health system built and analyzed population reports to review the potential return on investment for an outpatient palliative program.

Informing the next step

With the new data and reports in hand, the health system proposed an outpatient palliative care service line to its board of directors, and the board approved it. Now Carson Tahoe Health offers a palliative care/heart failure chronic disease management clinic that sees patients within five days of discharge.

Payers can deploy advanced analytics on top of their EDWs to enable reliable, faster decision making across the organization, and to enhance the value analytics teams can deliver. But with numerous business intelligence needs and stakeholders, prioritizing can be challenging.

We recommend the following four-step approach:

Align Analytics Initiatives with Business Priorities

Begin by identifying the strategic initiatives and business activities that could be most positively impacted by enhanced analytic insights. Some questions to consider include:

What are the key business imperatives?

Where can the greatest impact be made with support from advanced analytics?

Which business functions and stakeholders

require more timely information?

Identify the Analytics Required to Meet the Business Needs

With specific business priorities in mind, the next step is to determine what analytics are needed and how they’ll be visualized. You’ll want to assess the current suite of analytic tools and capabilities employed to address stakeholder needs including:

Grouping methodologies

Risk and severity models

Clinical rules

Reference data

Determine the Timeliness of Reporting Needs

As advanced analytics are selected for the analytic environment, payers should also evaluate their fit with existing business intelligence tools and capabilities. A few questions analytics leaders can ask to get started include:

Are analytic data marts easily accessible to analytics teams?

How current will the data need to be for various business reporting subject areas?

Would a conformed dimensional warehouse model speed user analysis and allow root cause to be evaluated?

Monitor and Adjust

Implementing a comprehensive EDW and advanced analytics strategy will likely be an iterative undertaking. That’s why it’s important to view your EDW and analytics initiatives as an ongoing process that doesn’t need to be perfect to get started. Regardless of where you are in the EDW-analytics journey, you’ll want to designate time quarterly or bi-annually to revisit the analytics roadmap and evaluate whether needs have changed.

In today's complex healthcare landscape, the path to success for payers will likely require a greater reliance on enterprise data and the critical insights that can be derived from that data. Licensing proven analytics that can be layered on top of the EDW can help accelerate time to insight. Click here to learn more about our new solution, Flexible Analytics.